A centre of expertise in digital information management

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Facing the Data Challenge : Institutions, Disciplines, Services & Risks

Dr Liz Lyon, Director, UKOLN, University of Bath, UK

Associate Director, UK Digital Curation Centre

1st DCC Regional Roadshow, Bath November 2010

This work is licensed under a Creative Commons LicenceAttribution-ShareAlike 2.0

Overview1. Facing the data challenge :

Requirements, Risks, Costs

2. Reviewing Data Support Services : Analysis, Assessment, Priorities

3. Building Capacity & Capability : Skills Audit

4. Developing a Strategic Plan : Actions and Timeframe

Institutional Diversity

http://www.flickr.com/photos/mintchocicecream/7491707/

Facing the Data Challenge

Case studiesOxford, Cambridge, Edinburgh, Southampton

Based on DCC Curation Lifecycle Model

Disciplinary Diversity

eScience Case studies

http://www.flickr.com/photos/30435752@N08/2892112112/

SCARP Case studies

• Atmospheric data

• Neuro-imaging

• Tele-health

• Architecture

• Mouse Atlas

http://www.dcc.ac.uk/sites/default/files/documents/publications/SCARP%20SYNTHESIS.pdf

Recommendations:

• JISC• HE & Research funders• Publishers & Learned societies• HEIs and research institutions• Researchers & scholars

http://www.data-archive.ac.uk/media/203597/datamanagement_socialsciences.pdf

http://opus.bath.ac.uk/20896/1/erim2rep100420mjd10.pdf

• Quick & simple deposit• Software tools • Laboratory archive

• Crystallography community engaged• ‘Embargo’ facility• Structured foundations• Discoverable & harvestable

Data Curation Profiles

Exercise 1a: Gathering requirements

• What are the researchers’ data requirements? • What datasets exist already? Standards?• What are their data priorities? Skills?• Research methodologies? Plans?• Equipment and instrumentation? Formats?• Where are the “pain points”?

• How will you find out? Approaches to use?• How will you use the information?

Exercise 1b: Motivation, benefits, risks• What are the RDM drivers and enablers for

research staff and post-grad students? • RDM drivers and enablers for Libraries / IT /

Computing Services / Information Services?• RDM drivers and enablers for the institution? • What are the barriers? What are the risks?• How will you articulate the benefits?

• How will you find out? Approaches to use?• How will you use the information?

Exercise 1c: Costs & sustainability

• What are the costs associated with RDM? • For the researcher?• For the institution?• Direct / indirect costs? Fixed / variable costs? • What cost data already exists?• What time horizon are you considering?

• How will you find out? Approaches to use?• How will you use the information?

• Survey e.g. Oxford, Parse.Insight• Focus groups : semi-structured interviews• Case studies departmental / disciplinary • Joint R&D projects• Data champions in departments• Data Preservation readiness : AIDA tool• Data audit / assessment : DAF tool

Requirements gathering: Approaches and tools

Benefits:

Prioritisation of resources

Capacity development and planning

Efficiency savings – move data to more cost-effective storage

Manage risks associated with data loss

Realise value through improved access & re-use

Scale:Departments, institutions

Dealing with Data Report : Rec 4

• DAF Implementation Guide October 2009

• Collating lessons of pilot studies

• Practical examples of questionnaires and interview frameworks

• DAF online tool autumn 2010

http://www.data-audit.eu/docs/DAF_Implementation_Guide.pdf

Methodology

http://www.data-audit.eu/DAF_Methodology.pdf

Data Audit / Asset Framework pilots May-July 2008

http://sudamih.oucs.ox.ac.uk/docs/Use%20of%20the%20DAF.pdf

http://eprints.ucl.ac.uk/15053/1/15053.pdf

Some lessons learned….

“CeRch had four false starts before finding a willing audit partner”“Pick your moment” ….“Timing is key” (avoid exams, field trips, Boards…)

Plan well in advance!“Be prepared to badger senior management”

Little documentation/knowledge of what exists:“a ni ghtmare”

Defining the scope and granularity is crucial

Collect as much information as possible in interviews/surveys

Variable openness of staff and their data

Identifying risks• Data loss (institution, research group,

individual)• Increased costs (lack of planning, service

inefficency, data loss)• Legal compliance (research funder, H&S,

ethics, FoI)• Reputation (institution, unit, individual)

http://foiresearchdata.jiscpress.org/

Freedom of Information FAQ (Draft)

Sustainability:Who owns?Who benefits?Who selects?Who preserves?Who pays?

Dimension 1

Direct Indirect (costs avoided)

Dimension 2

Near-term Long-term

Dimension 3

Private Public

Benefits Taxonomy: Summary

Keeping Research Data Safe2 Report: April 2010

KRDS• Which costs?• Effect over time?• Benefits taxonomy• Repository models• Case studies• Key cost variables• Recommendations

• User Guide, business templates forthcoming 2010

Reviewing Data Support ServicesAnalysis, Assessment, Priorities

1. Scale, Complexity, Predictive Potential

2. Continuum of Openness3. Citizen Science4. Credentials, Incentives,

Rewards5. Institutional Readiness &

Response6. Data Informatics Capacity &

Capability

http://www.ukoln.ac.uk/ukoln/staff/e.j.lyon/publications.html#november-2009

•Open Science at Web-Scale

A centre of expertise in digital information management

www.ukoln.ac.uk

1. Leadership 2. Policy 3. Planning

4. Audit

6. Repositories & Quality assurance

8. Access & Re-use

10. Community building

9. Training & skills

Data Informatics

Top 10

5. Engagement7. Sustainability

Exercise 2: Analysis, Assessment, Priorities

• Institutional stakeholders?• Data support services?• Range, scope, coverage?• Gaps?• Fitness for purpose?• Timeliness?• Resources?• Skills?

• SWOT

Strengths Weaknesses (Gaps)

ThreatsOpportunities

Digital Preservation Policies Study

High-level pointers and guidance

Outline policy model/framework

Mappings to institutional strategies

ExemplarsReport October 2008

State-of-the-Art Report : Models & Tools (Alex Ball, June 2010)

• Data Lifecycles• Data Policies (UK) incl DMP• Standards & tools• Data Asset Framework (DAF) • DANS Seal of Approval• Preservation metadata• Archive management tools• Cost / benefit tools

Jeff Haywood, RDMF V October 2010 http://www.dcc.ac.uk/sites/default/files/documents/RDMF/RDMF5/Haywood.pdf

Jeff Haywood, RDMF V October 2010 http://www.dcc.ac.uk/sites/default/files/documents/RDMF/RDMF5/Haywood.pdf

Jeff Haywood, RDMF V October 2010 http://www.dcc.ac.uk/sites/default/files/documents/RDMF/RDMF5/Haywood.pdf

Assessing cloud options

3 JISC Reports in 2010 :• Technical Review

• Cloud computing for research

• Environmental & Organisational issues

• North Carolina universities

• Cyber-infrastructure project

• Data cloud across three campuses

• “regional”

• Policy & practice

Policy

• Data types, formats, standards, capture• Ethics and Intellectual Property• Access, sharing and re-use• Short-term storage & data management• Deposit & long-term preservation• Adherence and review

Planning Dealing with Data Report : Rec 9

http://www.dcc.ac.uk/dmponline

DMP OnlineCurrently updating Version 1.0

Checklist questions mapped to funder’s data requirements

Checklist for a Data Management Plan

Slide : Martin Donnelly, DCC

DMP Online v2.0 (coming soon)

• Cleaner interface• Funder-specific guidance• Versioning feature• CSV output

Slide : Martin Donnelly, DCC

http://www.dcc.ac.uk/dmponline

DMPs next steps?

• Embed DMPs in funder policies & research lifecycles as the norm

• Code of Conduct for Research• Assess & review DMPs (not just

the science content of proposals)• Educate reviewers (DCC guidance

for social science in prep)• Manage compliance of researchers• Infrastructure to share DMPs

• Integrate in institution research management information system

Building a University Data registry…

Building Capacity & Capability

Data challenges?1. Data management plans2. Appraisal: selection criteria3. Data retention and handover4. Data documentation: metadata,

schema, semantics5. Data formats: applying standards6. Instrumentation: proprietary formats 7. Data provenance: authenticity8. Data citation & versions: persistent IDs 9. Data validation and reproducibility10. Data access: embargo policy11. Data licensing12. Data linking: text, images, software

Exercise 3: Skills Audit• What skills do you have in house?• What are your strengths? Core data skills?• Gaps? Do these matter?• Can / should they be developed?• How? Resource implications?• Other sources of expertise?• Key partnerships?• Team science roles?

Skills AuditSkill Source / Gap Comment

• Be specific• Prioritise core skills

Data Access & Re-use

“Community Criteria for Interoperability”(Scaling Up Report 2008)

• Domain data format standard: CIF• Domain data validation standard: CheckCIF• Metadata schema: eCrystals Application Profile

http://www.ukoln.ac.uk/projects/ebank-uk/schemas/

• Crystallography Data Commons: TIDCC Data Model in development

• Domain identifier: International Chemical Identifier • Citation & linking: DOI

http://dx.doi.org/10.1594/ecrystals.chem.soton.ac.uk/145

• Embargo & Rights http://ecrystals.chem.soton.ac.uk/rights.html

Data Licensing

• Bespoke licences• Standard licences• Multiple licensing• Licence mechanisms

• Forthcoming 2010

What to keep?

Repositories

Quality AssuranceTrust

Standards

Audit and certification tools

• TRAC

• DRAMBORA

• PLATTER

• NESTOR

• DANS Data Seal of Approval

Sustainability

PREMIS Data Dictionary

OAIS

• Representation Information

• Registry/Repository RRORI

http://www.loc.gov/standards/premis/

Data citation

Training

• Consortial• Institutional• Departmental

• Laboratory• Project

• Library• Computing Services

• Research staff / postdocs• Postgraduate students

“excellent : probably the best course I have been on since starting my role as an Informatics Liaison Officer”

Research Data Management Forum http://www.dcc.ac.uk/data-forum/

1) Roles & Responsibilities 2) Value & Benefits

3) Sensitive Data: Ethics, Security, Trust 4) Economics of Applying & Sustaining

digital curation

• Online resources• Includes training for• Data handling• Software• SPSS, NVIVO

• Live arts• Department of Drama• Researcher-practitioner focus

Embedding data informatics education...faculty & LIS...

Doctoral Training Centres

Developing a Strategic Plan

Optimising organisational support

• Organisational structures• Library / IT / IS / research support structure• Where does data management fit?• Leadership?• Co-ordination?

• Roles : data librarian, data manager, research support officer, data scientist, data curator...

• New roles?

New data support structures

Exercise 4: Actions and Timeframe

• Vision and Objectives: Are they clear?• Organisational structures: Fit for purpose?• Library / IT / IS structure : Is it optimal?• Roles : who is best placed to take action?• Responsibility : for each service / activity?• Priorities : what will you stop doing?• Resources : Do you need to bid for funding?• Partnerships : Who do you need to talk to?• Plan: What? Who? How? When?

Actions and TimeframeShort-term0-12 months

Medium-term12-36 months

Long-term>3 years

• Identify quick wins• What can you do tomorrow?

Take homes1. Understand the research data

requirements of your campus / institutional consumers

2. Agree research data service delivery priorities

3. Define data roles and responsibilities

4. Collaborate and strengthen the data support provided

5. Be pro-active! Engage! Be part of team science!

http://www.pnl.gov/science/images/highlights/computing/biopilotlg.jpg

Chicago Mart Plaza, 6-8 December 2010